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Record W4409699806 · doi:10.1186/s40900-025-00706-2

Addressing power imbalance in research: exploring power in integrated knowledge translation health research

2025· review· en· W4409699806 on OpenAlexaffabout
Jacqui Cameron, Anita Kothari, Renee Fiolet

Bibliographic record

VenueResearch Involvement and Engagement · 2025
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsWestern University
FundersUniversity of Wollongong
KeywordsKnowledge translationPower (physics)Knowledge managementPsychologyComputer sciencePhysics

Abstract

fetched live from OpenAlex

Integrated knowledge translation (IKT) is a knowledge translation framework that focuses collaboration between researchers and knowledge users (KUs) to generate research findings. KUs can be policymakers, clinicians, or those with lived experience who partner with researchers. While advocated as an approach that democratizes research and reduces power imbalance between researchers and KUs, it is not known if the implementation of IKT by health researchers actively addresses power imbalances. The aim of this study was to review research using an integrated knowledge translation approach to explore how power is addressed within these research studies. By looking broadly at how the studies addressed/described/discussed/dismantled power we explored examples of when this was done well and not so well, exposing the assumptions sometimes made by researchers. We drew from systematic review procedures combined with a modified critical discourse analysis (CDA) lens. We searched Medline, PsycINFO, CINAHL, Scopus, Social Science Database, SocIndex and Google Scholar for English language studies that focused on IKT and power. Data were extracted on study characteristics and a modified CDA which included questions in relation to power (e.g., description of power, phrases used to describe power, evidence of power dynamics, strategies for addressing power imbalances) and end user engagement (e.g., Did they ask KUs how they wanted to be involved? Did they engage in reflection with KUs? Did they discuss dissemination strategies with KUs). Eleven studies were eligible after screening 381 titles and reviewing 40 full-text studies. The use of IKT to address power varied significantly, revealing both positive examples as well as some missed opportunities to address power imbalances from study inception to dissemination. Revisiting the use of IKT to examine how power is defined, shared, and managed in relationships with KUs could provide valuable insights. Using a CDA framework to explore these dynamics would indeed address the nuances of power in research contexts. Future research should focus on developing strategies to effectively implement IKT to address power imbalances, leading to research that has a better chance of being useful, usable and used in practice. One of the difficulties of doing research is understanding and managing the power difference between researchers and knowledge users (community members/those impacted by disease/service providers). When power imbalances are not managed well in research teams, the results may not be as beneficial to its knowledge users because it may not be relevant, and further, power imbalance can negatively impact knowledge users’ experiences of engaging in research. Some researchers are trying to ensure there is more equality in research and explore how to address power differences within their own work. There are different ways to help researchers collaborate with knowledge users. One method of working with knowledge users in research is called Integrated Knowledge Translation (IKT), which started in Canada in the 1990s. IKT involves everyone in the research process working together from the start and is focused on ensuring that those who will be using research also inform its production. The aim of the current study was to review studies using an integrated knowledge translation approach to explore how power is addressed within these research studies. By broadly examining how the studies addressed, described, discussed, and dismantled power, we were able to identify various examples of effective and ineffective approaches. In the eleven papers we assessed, power was not always addressed or explained well. When it was, discussion about power was found in the background of the paper, or in some sections of their work rather than a strong focus of the work, suggesting there are many opportunities for researchers to better address power.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaScience and technology studies
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.239
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.815
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2390.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0110.012
Science and technology studies0.0040.001
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0010.015
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.993
GPT teacher head0.814
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

Science and technology studiesMetaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designTheoretical or conceptual · Qualitative
DomainMethods
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2025
Admission routes2
Has abstractyes

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